Karol Bartsch, one of the first clients of SimSched, has over twenty-five years of experience in open cut iron ore and gold mining industry in production and planning environments. He also have extensive experience as a Lead Competent Person for reporting of ore reserves under JORC and SEC rules and ore reserves and mine planning risk assessment under SOX. Recently, Karol produced a case study using SimSched DBS, which we reproduce here with his authorization.

Waste Dump Sequencing with SimSched DBS

“SimSched DBS is an open pit optimization package that selects maximum NPV pit shell while generating a mining schedule. SimSched offers optimization of multi element models with alternative processing routes for each block, with stockpile/reclaim option for any potential ore. Waste material can also have alternative dumps defined. The economic value (or costs) of each block will be considered in selecting processing route or a destination.

While testing SimSched, I got interested to see if a waste dumping sequence optimization can be generated and later connect it to the optimum mining (ex pit) schedule and further, if such a schedule could improve cost estimation ahead of mine plan optimization (optimum pit size and production schedule). The waste block model would be prepared beforehand and then dumping schedule generated.

The waste scheduling test was based on the following assumptions:

only waste dumping operating costs were considered;

no allowance for change in mining fleet capacity over time (no additional CAPEX);

minimizing Net Present Cost of waste dumping is the main optimization objective;

the waste dump block model was constructed on flat topography.

Waste dump built on a flat surface is constructed layer by layer from the lowest to the highest level, ramps and access roads are built to connect ramp exit at each level and the tip head (dump edge) on the same level. If we turn over the waste dump and reverse the dumping activity to a mining activity, the dump extraction would look just like pit excavation.

A spreadsheet model of a 3 level waste dump has been designed to allow for changes in dump block size, including height of a lift, location of ramp to the first level and location of ramp exits on every other dump level. Dumping cost include flat haulage of waste to the dump ramp starting point (i.e. pit to dump), and also to each block on every level. It is worth noting that while flat haul is cheaper initially, up to a certain distance, then it becomes more economical to start dumping on a level higher up. Since SimSched is essentially a pit optimization tool, it requires certain fields to be available in the model:

location of each block is represented by iX, iY and iZ indices;

value element grade in PPM or % (for waste I used 1 for a block to receive waste and 0 for blocks outside the dump);

economic value for a process and economic value for waste;

rock density and pit slopes - each can be a field in the model or a default value provided in one of the entry screens.

Economic value for 'processing' waste is directly related to the dumping costs, the lower the cost, the higher the value to make such a block more attractive to be used earlier.

The optimization allows for changes in minimum mining width - or a minimum width of a dump cell, this can prevent the dumping face to change erratically within the same time period. The vertical rate of advance can help to promote raising the dump height faster, should there be a real need - perhaps dump topography other than flat.

Modelling areas of a dump to store materials of different chemical or physical properties can be set-up as different (alternative) processes. Dumping (processing) capacities can be controlled using period constraints.

Provided a flexible waste dump model is created, either in a general mining package or a spreadsheet, the user can test various dump configurations such as dump block size, final dump height vs. lateral expansion, location of the main dump entry point as well as location and directions of ramps for each level.

Once the optimum dumping sequence is defined, the waste cells (sum of all blocks utilized in a period) can serve as a better guide to estimate waste costs for the pit optimization exercise.

The SimSched DBS by MiningMath is a truly remarkable product, allowing the user not only to obtain pit shape that maximizes the NPV, but also simultaneously prepare mining schedule that honors block model properties, geotechnical pit slopes, processing rates and recoveries, drop down rates and user defined constraints. Besides it helps to better define costs of mining waste and optimize dumping sequence.

I have high regards for the MiningMath team not only for the work to develop SimSched, but also for the attention they give to promptly answer queries and issues raised by the user.

I wish MiningMath all the best to continue with their efforts to give the practitioners a real alternative pit and sequence optimization tool ”

Veronica Gil-Costa is a professor of Design Software and Mine Planning at the National University of San Luis, Argentina. Veronica and her working team are in continuous search for technological solutions to improve and facilitate the work of engineers at mine sites, so they decided to include SimSched as part of their course. This enables students to have access to knowledge of new trends and how these tools can improve the mine planning process.

Incorporating SimSched in the formation of Mining Engineers at the National University of San Luis

“In this first test stage, the use of the software was introduced using the data provided (Marvin case study). Following the sequence of steps required to run the simulation allowed students to experience the software interface, including how data can be loaded.

It was important to realize the ease and speed to create different scenarios by only modifying some parameters and without having to load all the data again. Also the automatic export of results to an Excel spreadsheet is an advantage when interpreting and representing the outputs.

The generic CSV format in which the optimized model and surfaces are automatically saved, allows the option of working in other software.

In the course of Design Software and Mine Planning, now in its fourth year, the first task of the students will be to present the characteristics of different existing mine planning software on the market and compare them to the new technological trends in SimSched. This is then secondly followed by using the software on a real database to see the results (and the difficulties that may appear) and work together with students to learn how to incorporate the software on a specific case study with its own peculiarities.

The purpose of having this software is to enable its use, in the Operation III course, where students has to define how production schedules vary depending on basic design parameters of the pit. Using SimSched software, where they can display different results quickly, allows them to better understand the consequences and effects of their decisions.”

Dr. Luis Martinez is an engineer with over 18 years of experience in mining engineering, geostatistics, advanced quantitative risk analysis, financial and economic and project evaluation and decision making analysis. Martinez is the founder and General Manager of R&O Analytics. Recently, Martinez published a white paper on LinkedIn, which we reproduce here with his authorization:

Innovation and Technology to Improve Open Pit Mine Plan and Design Optimization

“In mining, the change in technology, i.e., processes and software, does not happen fast but it takes its time, around 10 to 15 years as miners are very conservative. Indeed, throughout the years new processes and software technologies have appeared and replaced the traditional ones because of their benefits when applying them in real life.

To name a couple of them, we could mention Geostatistics techniques (e.g., kriging and simulation) which are now standard for resource estimation, overruling the well-known polygon and inverse distance techniques, and in open pit mining the Lerchs and Grossmann (LG) algorithm for open pit design which overruled the well-known floating cone method (and variations); the LG algorithm is currently standard for pit design optimization and it is implemented in most, if not all, off-the-shelf mine plan and design software packages. In respect to open pit mine plan and design, the traditional optimization processes is done by following the general steps:

Apply cut-off grade optimisation, based on Lane’s theory, to generate the yearly (long term) production scheduling – this is done by maximising the Net Present Value (NPV) of the mine operation, considering the time value of money and obeying operational constraints such as mine, mill and refining capacities. Something important to observe is that the process of cut-off grade optimisation depends on both the ultimate pit and phase/cutback designs, which depend on the initial nested pit-shells.

Here the mandatory question was if it could be possible to generate the long-term mine production scheduling of an open pit mine project without worrying about the nested pit-shells and phase/cutback designs.

In the search for companies/products that are using high-end and academically proven off-the-shelf frameworks for mine plan and design optimization, I've found MiningMath with its recently released software SimSched. The 'SimSched' mining software is a new software technology for open pit mine plan and design optimization, which uses an innovative algorithm, based on operation research techniques (a surface constrained method) to plan and design the long-term production scheduling, which includes the ultimate pit, of an orebody. The process maximizes the project’s net present value (NPV) while satisfying operational constraints such as mill and mining capacities, i.e., it accounts for the time value of money when doing the optimization.

The contribution that the SimSched software/process brings to the mining industry is that conversely with traditional processes for open pit mine plan and design, that are based on the block, bench, pit-shells and cutback resolution, the SimSched only uses the operational and physical constraints at the block resolution to estimate the 'best' long term production scheduling, including the ultimate pit, of an open pit mine project – jumping in this way the many steps that traditional processes do to estimate the final pit plan and design and, consequently, avoiding the dependency on both the pit-shells and cutback designs.

In this case the optimizer selects the best blocks (ore and waste) within the block model that will maximize yearly production cash flows and consequently project’s NPV – this is done obeying physical constraints such as slope angles, minimum working space, among others.

Although the application of operation research in open pit mine plan and design is not new, the SimSched process/algorithm makes it tractable enough to be applied in real life in an efficient way, i.e., with minimum time and human effort, while providing a clear view of the different spatial aspects of the mine project that will assist mine designers to further develop the project.

Although still in a beta version, and new to the mining industry, I believe the SimSched software will become an important tool for open pit mine plan and design assisting mine planners and managers to optimize their projects.

The implementation and use of the SimSched in open pit mining will also bring new challenges and questions about traditional optimization processes especially for multi-elements, risk analysis and others, which I expect will provide the basis for further improvement.

Currently, different MiningMath’s associate companies around the world are testing the SimSched (http://www.simsched.com/) process by analyzing the results obtained and comparing them with the results obtained from traditional software techniques – highlighting its advantages and benefits while identifying areas for improvement. We hope definitive results will be available soon for everyone to read. ”

“Access to SimSched DBS and all its advanced functionalities provides future Mining Engineers and Researchers a more analytical and comprehensive foundation concerning to the development and conception of mining projects.”

Edmo Rodovalho is a researcher and Professor at Universidade Federal de Alfenas, Brazil (UNIFAL). He is a specialist in mine planning and has operational experience in relevant companies such as Vale and CSN (Companhia Siderúrgica Nacional). Mr. Rodovalho has followed the development of SimSched since its initial stages, and he shared the following testimony regarding his professional relationship with MiningMath:

A New Generation of Engineers

“My contact with MiningMath happened through scientific and academic cooperation. Since this partnership started, its professional relevance for the mining business area was clear. Furthermore, the company has a strong commitment to meeting deadlines and achieve goals.

The achievements of the MiningMath team, can be attributed to the multidisciplinary structure and openness to engage in partnerships with universities and research centers. Based on this knowhow, the company has the capability to supply the most up to date products and potential to generate positive results.

The first product that we tried was the SimSched Pit Optimizer. It was used in academic research activities. Rapidly, it became clear that SimSched brought improvements to both academia and the mining industry.

After that, we began to use SimSched Direct Block Scheduler, which offers a new approach to optimization and mine scheduling. Despite these great advances, firmly entrenched concepts, current techniques and research consolidated by mine industry are not left behind. Instead, by measuring results obtained through the application of mixed integer programming with the addition of heuristic properties (as opposed to traditional techniques) this exercise illustrates the opportunities for financial leverage in the results of mining enterprises. Issues related to financial viability of mineral deposits are being increasingly discussed in both academia and in society.

Access to SimSched DBS and all its advanced functionalities provides future Mining Engineers and Researchers a more analytical and comprehensive foundation with respect to the development and conception of mining projects. Given that new tools and techniques implemented by MiningMath through SimSched DBS demand constant interaction, the MiningMath technical team injected their initiative and support to the academic activities, as well as provided access to updates and tool releases.”

“...Solving the optimisation in a single pass has a number of potential benefits as the optimised pit limit can account for the time value of money, cut-off policy and mining constraints such as pit bottom width and minimum mining width...”

Matthew Randall is an independent consultant from the United Kingdom and a Mining Engineer with over 35 years of experience in mine planning. Recently, Matthew published an abstract in LinkedIn of a study conducted evaluating NPV Scheduler (NPVS) and SimSched Direct Block Scheduler (DBS). With his permission we quote here Matthew’s opinion:

A New Approach to Schedule Optimization?

“I have been testing SimSched Direct Block Scheduler (SimSched DBS) alongside Datamine’s NPV Scheduler (NPVS) in order to establish whether the SimSched DBS approach results in any significant changes to the resulting schedule that might benefit the project.

The dataset I am using is from a gold deposit with 3.6 million blocks that comprises of two distinct pits that will be mined simultaneously. The schedule incorporates a cut-off policy that attempts to maximise NPV by stockpiling and reclaiming low grade material as required.

A typical solution time with SimSched DBS for this project was 16 minutes, which was quite acceptable and faster than the sum of the required steps in NPVS. This was very encouraging in view of the complexity and size of the problem.

The preliminary results indicate that the overall size of the pit is very similar with either package but the mining sequence and cut-off policies differ considerably. These differences can be explained by the fact that NPVS adopts a step-by-step process of optimisation that requires the pushbacks to be generated from the pit optimisation results, followed by scheduling of the Pushbacks, and finally optimisation of the cut-off policy with the Mine Flow Optimiser (MFO) module of NPVS. In comparison SimSched DBS solves the pit limit and schedule optimisation problem in a single step.

Solving the optimisation in a single pass has a number of potential benefits as the optimised pit limit can account for the time value of money, cut-off policy and mining constraints such as pit bottom width and minimum mining width. This can lead to a smaller (higher NPV) pit that eliminates material that is uneconomic due to deferred revenue compared to incurred mining cost. It also leads to mining sequences that are practical in terms of mining constraints and production targets. The current limitations of the Beta version of SimSched DBS of course do not give it the rich functionality of mature products such as Whittle and NPVS, but are these being addressed in a methodical fashion.

By running SimSched alongside NPVS and Whittle, it can be shown that there is considerable potential to explore alternative mining strategies with SimSched DBS that can lead to radically different solutions. As ever it is hard to predict how a particular deposit will behave under a given set of constraints, but I believe SimSched provides a very useful insight into this problem by removing some of the software limitations of other packages that rely on a step by step optimisation methodology.”

Ruben Horbach is an independent geological consultant with over 40 years of experience in mineral exploration and deposit evaluation. Ruben tested our SimSched DBS beta version and recently sent us an email sharing some of his experience with the software:

SimSched DBS: A Revolutionary Software

“Through the support team, that has been giving me the support in the usage of SimSched DBS beta versions, I would like to thank MiningMath for the opportunity of testing such a revolutionary software used in multiple scenarios simulations of open pit mine planning scheduling projects.

From the tests I’ve performed, using block models with dimensions varying from tens of thousands until almost a million blocks, taking into account the traditional algorithms of simulation and mine planning, I was able to find an incredible shorter processing time, considering that usually I would need to go through a series of complex steps for a non-specialist like me. Aligning with this improvement, the results found had such a quality comparable to the already established software.

Currently, results obtained within SimSched are able to perfectly integrate with other software packages in common use, and based on information that I have received, it is expected that soon the new SimSched implementations will allow even better interoperability with commonly used software for resource estimations and mineral reserves.

I wish all the best of success for the MiningMath team in this important project.”

“…the tool has allowed us to improve the operational phase design stage, by viewing the contouring lines of the optimized mine plan periods, to make more accurate decisions and achieve geometries that meet operational requirements.”

Mauricio Brücher is a mining engineer who graduated from the University of Santiago, Chile. In addition, he has a Diploma in Business Strategies obtained from the Adolfo Ibáñez University (Chile). He has 16 years of work experience in the mining industry. His career includes positions as study manager, mine planning, strategic planning, university teacher, project evaluation, budgets and KPI control. Since 2009, he has been a member of the Australian Institute of Mining and Metallurgy (AUSIMM). Since mid-2015, he has been managing partner at InnovaMine, a mining consulting group created together with Juan Camus, which seeks to create value for its clients based on the search for innovative solutions, especially in the area of mine planning.

The Long-Awaited Strategic Planning Tool

“SimSched DBS is the tool that many mining planners have been waiting for. It allows finding an optimum final pit envelope as well obtaining a mining sequence that considers the basic operational constraints when generating a mining sequence. Among the aspects considered are the mine sinking rate, minimum mining widths and most importantly, the time factor associated with mining rates, plant feeding rates and the discount rate applied to each project independently. This, in turn, allows establishing the most important economic metrics of the business, in terms of mine and plant capacities, CAPEX and project value.

To have a tool that allows you to review the mine plan, including the mining sequence and final pit by changing the basic planning parameters, it is perhaps the most important achievement. This is especially relevant since mine planning is a dynamic process and so are the main mining variables such as the mining sequence, which depends on prices and other variables that govern the planning process. It is worth noting that the vast majority of current commercial mine planning tools, only optimize a mine plan from a "static and previously defined" sequence. This is usually created using the Lerch Grossman algorithm, by varying the commodity price or operating costs.

Another important advantage of this tool is that the optimization is always associated with a particular mine plan, which allows the review, in a single step, of both the final pit limits and the interim economic flows and materials. This enables the rapid assessment of the project sensitivities when changing boundary conditions.

At InnovaMine, we have used DBS in different real projects, and have obtained good results in mining sequences and project cash flows. Another important benefit is that the tool has allowed us to improve the operational phase design stage, by viewing the contouring lines of the optimized mine plan periods, to make more accurate decisions and achieve geometries that meet operational requirements.

We know that the DBS tool is in an early stage of development, but we also believe in the potential that this tool could have with the new features that the MiningMath team is committed to develop in the medium term. It is with this challenge that we can firmly support MiningMath to find innovative solutions that add value to our clients’ projects.”

“It is not necessary to compute the cutoff grade beforehand, SimSched PO has the algorithm that decides the best destination of the block (process, waste or not mined), maximizing the undiscounted cash flow.”

José Gregorio Freites is a mining engineer from Universidad de Oriente, Venezuela. He has over 20 years of experience in the mining industry and his career includes positions in the areas of mine planning, strategic planning, bulk explosives manufacturing, drilling and blasting. José Freites is the founder of Cursos GeoMin, which is a web based platform for Mining and Geological courses.

Run either a Pit Optimization or a Long-Term Mine Plan with only a few mouse clicks.

“MiningMath has two products for mine planners: a) SimSched Pit Optimizer (PO) and b) SimSched Direct Block Scheduler (DBS). I consider both SimSched PO and SimSched DBS easy to use, users can run either a pit optimization or a long-term mine plan with a few clicks of the mouse. This is very important for Cursos GeoMin because the process of learning the software requires a minimum effort by the user/participant and both SimSched PO and SimSched DBS are easy to be applied in real mining projects. The linear formulation of the long-term mine planning problem is transparent to the final user as he just needs to fill a few inputs, the results are easy to visualize and can be imported into any Mine Planning Software that reads a CSV file.

The traditional approach used by Lerchs-Grossmann algorithm, Max Flow algorithm or Moving Cone heuristic requires a cutoff grade calculation in order to decide the destination of the block during the pit limit computation. SimSched PO goes beyond that! SimSched PO is a free software for pit limit computation based on a mixed integer linear programming (MILP) and surface constrained method; this technology is available to universities and mining Industries. It is not necessary to compute the cutoff grade beforehand, SimSched PO has the algorithm that decides the best destination of the block (process, waste or not mined), maximizing the undiscounted cash flow. I consider that SimSched PO is an excellent complement to RecMin software (which implements the Moving Cone heuristic). Both are free to use, SimSched PO brings the optimum pit limit respecting a minimum bottom width and RecMin can be used to add roads to the pit and other calculations and designs.

SimSched DBS implements MILP and other heuristics to solve the long-term mine planning problem, it solves the schedule optimization problem in a single step: it is not necessary to go through the traditional approach to break the long-term mine planning problem in different phases. SimSched DBS computes the mining schedule maximizing the Net Present Value (NPV) directly from the block model and it provides a solution in a reasonable time frame. Although still in a beta version, it is a promising technology that could change the way the long-term mine planning problem is focused currently; SimSched DBS is in constant development and I would like to see in a future version the release of the blending option and the possibility to deal with multiple block models to run simultaneous optimization.”

“…we thank the technical support team since they were always willing to provide their assistance in a prompt and efficient manner. Additionally, we received a visit of a member of the technical team in our country, which provided us with assistance for a more efficient use of the software.”

SimSched DBS: a tool for the industry and academy

“The National University of Colombia Sede Medellín agreed to be an official academic partner of MiningMath, by means of the Mine Planning Investigation Group (GIPLAMIN), with the aim to have access to SimSched DBS software. This allowed the students to have an approach to an innovative tool and equipped with high technology in mine planning.

SimSched DBS software is a tool that allows, by means of providing input assumptions of a mine, the use of a mathematical model based on uncertainties that weren’t previously considered by the mining industry. It allows the consideration of data and real risks that can be controlled within time frames, enabling operational costs reduction and increasing the value of the mining project.

This beta version of the software permitted us to determine production schedules from a mathematical block model imported for a deposit, where our objective was to determine the final destination of each block based on their characteristics. The software proved user friendly and offered numerous functions implemented, in addition, allowed us to consider multiple scenarios through optimization steps simultaneously.

The work performed by the students of GIPLAMIN group using SimSched DBS mining software, consisted of analyzing the behavior of two economic variables (discount rate and rehandling costs) and three geometrics parameters (slope angle, size of the ultimate pit and vertical advance), in order to achieve the most optimal values for the exploitation design of a hypothetical open pit mineral deposit. For each of these parameters, a series of individual simulations were performed, yielding 5 optimal values. It was subsequently observed that it is possible to obtain a higher net present value (NPV) if these values are integrated. One of the most relevant conclusions of this work is that a greater extraction doesn’t always represent an increase of the NPV, but the opposite, it is possible that it drops drastically due to operation costs involved in a larger scale project. The challenge is to minimize operation costs while increasing the project’s NPV.

The group (GIPLAMIN) of National University of Colombia Sede Medellín made possible this approach thanks to the license provided by MiningMath for the beta version of the program, which was essential for the completion of the study. Also, we thank the technical support team since they were always available to provide their assistance in a prompt and efficient manner. Additionally, we received a visit of a member of the technical team in our country, which provided us with assistance for a more efficient use of the software.”

Jorge Lozano is co-founder of Inti Mining Smart Solutions (IMSS). He holds an undergraduate degree with the National Engineering University in the area of Mining Engineering and has represented Peru and the National Engineering University in regional programming competitions such as ACM Computer during his time at the university. He has worked in ore control, dispatch, dashboard development at Visual.net, short, medium and long-term mine planning and strategic planning at Barrick Pierina, Barrick Lagunas Norte and Antamina. He currently serves as Technical Manager for IMSS in Peru and Chile.

My experience with SimSched

“During 2016 I started using SimSched to strengthen strategic planning processes. I found that SimSched could be a powerful tool for the strategic analysis of reservoirs because it integrates many variables into a single process and that their mutual interaction provides better directives for the decision process.

During the last years I have worked on more than 10 mining projects in which I have been designing mines of different sizes and with different restrictions. This process was done using the traditional methodology, using Lerchs-Grossmann, and under the mental scheme that the optimization process is an iterative process to reach the best value, if we can find it. The experience from more than 5000 developed mine designs has given me the expertise to find the design that maximizes the value of a company, but I always wondered how to do it more efficiently? How to integrate the capacities and restrictions of the mining and metallurgical processes in a single step?

My first approach to the questions I asked in the previous paragraph was in a training of Blasor when I was working on Strategic Planning in Antamina, and I was pleasantly surprised to find tools that provided directives to follow to design strategies for exploitation. SimSched came to me at the end of 2015 and I was able to compare its capabilities with the projects I was doing. I saw in SimSched the birth of a new technology that could change the way of thinking and acting in the mining world.

In 2016 I founded Inti Mining Smart Solutions (IMSS) and in all projects I have tested the SimSched approach. This past year I have developed 10 projects in Peru and Chile, including plant and mine capacity analysis, IPCC mechanized systems, during which I have experienced the potential of SimSched. I have been able to reach 90% of the Best Case NPV in most of the projects leaving my clients very happy, not only with the results obtained but also with the integrated methodology that this system offers us.

Given the above, I recommend using SimSched on all the projects you do and I’m sure that the way you view mine planning will change radically.”

“…the timely assistance provided by the technical team of MiningMath is of great help to users of the software, since it allows clarifying doubts quickly. It’s outstanding its great willingness to support academic initiatives as it was in my case.”

Clíder Niño is a Mining Engineer from the Pontifical Catholic University of Peru currently working as a Junior Mine Planning Engineer at IntiMining Smart Solution (IMSS). He has also previously worked at MMG and Southern Peru Copper Corporation. His career includes experience in geomechanics, safety and short-term planning in underground and open pit mines.

I recommend its use

“The optimization methodology proposed by SimSched definitely has a clear advantage over current methods. Thanks to direct block scheduling, nowadays it is possible to perform complex analysis in a shorter time and with reliable results, without the need to carry out many iterations during the optimization process. Personally, I recommend its use because it is an excellent tool for strategic planning of open pit mines.”

In my case, I used SimSched to do my degree thesis, which consisted of maximizing the value of an open pit mine project through an optimal phase design and production plan based on the optimized guide that I obtained from the DBS. The results showed that, in spite of the operational restrictions presented in the case study, which decreased the value of the project, the NPV remained. This means that the mining direction proposed by the DBS achieves better results than traditional optimization.

Frequently asked questions

What is SimSched DBS?

It is a software application that uses innovative technology for direct block scheduling. The SimSched DBS aims to maximize the Net Present Value (NPV) of a project deciding, based on an imported block model, which blocks will be mined, when and what the destination of each block is.

It is possible to define multiple processing plants, stockpiles and waste dumps, respecting their capacities. It is also possible to set physical limits or force mining in certain regions by importing surfaces.

As the software has a flexible algorithm, it will be possible to include other restriction types in the future, such as blending for example.

OK, but why should I use SimSched DBS?

The direct block scheduler allows running a complete schedule directly from the resource block model, with no need to define a final pit, nested pits, pushbacks, cut-off grade optimization and stockpiles as would be required as part of a traditional full scheduling exercise. SimSched DBS will find a mining schedule that aims to maximize the NPV of the project, combining all the steps mentioned and optimizing all the periods simultaneously. Therefore, an experienced professional can test multiple scenarios by modifying parameters and advance other stages of his work, while SimSched DBS performs the entire optimization.

Is the generated solution operational, or only a mathematical result?

Each mining plan generated by the optimization respects important geometrical parameters, such as a minimum pit bottom width, a mining width and vertical rates of advance, which can be configured specifically for your project. Furthermore, SimSched technology generates surfaces
without geotechnical errors. The generated plans are close to the operational reality of the mine, which implies smaller variations in the parameters when ramps are designed.

In practice, how can I use SimSched DBS to scheduling optimization?

A block model, in CSV format, including indexes and economic values of the blocks is first imported followed by entering the primary parameters of the model and production restrictions via interface. Upon completion of these steps, SimSched is ready to perform the optimization.

The resulting surfaces will respect the user-defined parameters and a report will be generated with graphics containing the most important indicators.

To demonstrate the usage and power of the software, you can access our demo video
here.

Figure 1: Scheduling results performed by SimSched DBS. A- Optimized schedule, in which surfaces are generated and each color represents a period of mining / At the end of the optimization, production graphs (B), contents (C) and economic results (D) are generated.

Does SimSched DBS suit my project? What are the limitations of the current version?

The current version of SimSched DBS suits any open pit mining project that can be modeled with blocks of regular dimensions. If your project has multiple types of rock per block, there are ways to adapt the inputs to handle these cases. SimSched is 100% based on 64-bit technology and has an efficient algorithm, capable of handling tens of millions of blocks without requiring supercomputers or cloud computing.

To date, MiningMath has focused on developing the best algorithms; future versions will introduce more facilities for the user, including the development of plug-ins to mining softwares on the market.

I have a sub-blocked model. How could SimSched be used in this case?

If the model can be exported by dividing all blocks into sub-blocks, then we have a regular database formed only by sub-blocks and SimSched can run it. We perform regular tests successfully using models with tens of millions of blocks. For future versions, we are planning significant efficiency improvements.

OK, but what is the cost of this innovative technology?

What is the difference between SimSched PO and SimSched DBS versions?

The main difference is that the DBS version considers the impact of money over time: the NPV of the project is maximized considering a discount rate over the periods.

The PO version aims to maximize the undiscounted value of the project: the maximum profit that the project could generate if all the material were mined and processed today, generating an optimized pit that will not necessarily be the best solution, given the simplifications of this mathematical model.

SimSched PO is a simplification of the main algorithm in SimSched DBS and will continue receiving most of the new developments related to SimSched DBS, like blending restrictions.

Does SimSched DBS have the Lerchs-Grossman (LG) algorithm implemented?

No. LG is a brilliant algorithm for its time, but none of the new software need to implement it anymore. The technological advances have proven that new methods overcome some barriers that the LG faces. These days, any software that has the same mathematical model of LG implemented will rather implement an algorithm based on maximum flow rate (Max Flow) which can be run tens or hundreds of times faster than the LG. However, both LG and Max Flow have no flexibility to include other important restrictions such as a minimum pit bottom width or blending.

SimSched uses highly recommended technology currently in practice and inside research centers, being what is the most advanced, tested and available when talking about optimization. It was implemented using modern techniques based on mixed integer programming and heuristics. Its mathematical model is more realistic, for considering operational aspects and uses surfaces to return solutions that does not have any geotechnical errors. What in practice is mined are surfaces and not blocks. This type of technology has the flexibility to include other real restrictions, such as blending.

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